Knowee
Questions
Features
Study Tools

The average depth of a binary search tree is:*O(n^0.5)O(n)O(log n)O(n log n)

Question

The average depth of a binary search tree is:*O(n^0.5)O(n)O(log n)O(n log n)

🧐 Not the exact question you are looking for?Go ask a question

Solution

The average depth of a binary search tree is O(log n). This is because a binary search tree is a tree data structure in which each node has at most two children, referred to as the left child and the right child. For each node, all elements in the left subtree are less than the node, and all elements in the right subtree are greater.

In a balanced binary search tree, the path from the root to any leaf is log(n), where n is the number of nodes in the tree. This is the best case scenario.

However, in the worst case scenario, such as when the tree is a straight line (essentially a linked list), the depth is O(n).

So, the average depth of a binary search tree is generally stated as O(log n), but this assumes that the tree is reasonably balanced.

This problem has been solved

Similar Questions

Give the time and space complexity of the Tree Search version of Depth-First Search (DFS), in terms of the branching factor b and the maximum depth m of the search tree.Write your answer using big-O notation, and if you need to use powers then write them in TeX notation. For example, n squared would be written as n^2. If the algorithm has worst-case complexity n squared, it would be written as O(n^2).

What is the average time complexity for searching an element in a binary search tree?Group of answer choicesO(1)O(n)O(log n)Depends on the tree structure

Pick the average time complexity for finding out height of Binary tree

What is the space complexity of a Binary Search Tree if n is the number of nodes?O(1)O(log n)O(n)O(n log n)

The maximum height of a binary search tree is O(log n), where n is the number of nodes.Group of answer choicesTrueFalse

1/3

Upgrade your grade with Knowee

Get personalized homework help. Review tough concepts in more detail, or go deeper into your topic by exploring other relevant questions.